Fix pytorch recorder adapt_linear when using autodiff backend

[laggui]

Stumbled upon this issue when trying to load a record with PyTorchFileRecorder for a model using the autodiff backend.

Checklist

• Confirmed that run-checks all script has been executed.

Changes

The line below would panic with Can't convert a non leaf tensor into a tracked tensor when using the autodiff backend.

Param::from_tensor(weight.val().transpose());

That's simply because the parameter is being created from a tensor that is being transposed, an operation that is tracked by autodiff.

Solution: set require grad to false when creating the parameter from the tensor transpose.

Testing

Added autodiff unit test for complex model that includes a linear layer.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 86.33%. Comparing base (6522276) to head (79ab0ca).

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1576   +/-   ##
=======================================
  Coverage   86.32%   86.33%           
=======================================
  Files         686      686           
  Lines       78440    78451   +11     
=======================================
+ Hits        67714    67728   +14     
+ Misses      10726    10723    -3     

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[antimora]

Looks good to me. Thanks for catching it and fixing it.